Nejvíce citovaný článek - PubMed ID 35803199
Flavonoids exert potential in the management of hypertensive disorders in pregnancy
Significant limitations of the reactive medical approach in breast cancer management are clearly reflected by alarming statistics recorded worldwide. According to the WHO updates, breast malignancies become the leading cancer type. Further, the portion of premenopausal breast cancer cases is permanently increasing and demonstrates particularly aggressive patterns and poor outcomes exemplified by young patients with triple-negative breast cancer that lacks targeted therapy. Accumulating studies suggest the crucial role of stem cells in tumour biology, high metastatic activity, and therapy resistance of aggressive breast cancer. Therefore, targeting breast cancer stem cells is a promising treatment approach in secondary and tertiary breast cancer care. To this end, naturally occurring substances demonstrate high potential to target cancer stem cells which, however, require in-depth analysis to identify effective anti-cancer agents for cost-effective breast cancer management. The current article highlights the properties of flavonoids particularly relevant for targeting breast cancer stem cells to mitigate therapy resistance. The proposed approach is conformed with the principles of 3P medicine by applying predictive diagnostics, patient stratification and treatments tailored to the individualised patient profile. Expected impacts are very high, namely, to overcome limitations of reactive medical services improving individual outcomes and the healthcare economy in breast cancer management. Relevant clinical applications are exemplified in the paper.
- Klíčová slova
- breast cancer, cancer stem cells, non-responsiveness, predictive, preventive and personalised medicine, resistance, secondary and tertiary care,
- Publikační typ
- časopisecké články MeSH
- systematický přehled MeSH
Proliferative diabetic retinopathy (PDR) the sequel of diabetic retinopathy (DR), a frequent complication of diabetes mellitus (DM), is the leading cause of blindness in the working-age population. The current screening process for the DR risk is not sufficiently effective such that often the disease is undetected until irreversible damage occurs. Diabetes-associated small vessel disease and neuroretinal changes create a vicious cycle resulting in the conversion of DR into PDR with characteristic ocular attributes including excessive mitochondrial and retinal cell damage, chronic inflammation, neovascularisation, and reduced visual field. PDR is considered an independent predictor of other severe diabetic complications such as ischemic stroke. A "domino effect" is highly characteristic for the cascading DM complications in which DR is an early indicator of impaired molecular and visual signaling. Mitochondrial health control is clinically relevant in DR management, and multi-omic tear fluid analysis can be instrumental for DR prognosis and PDR prediction. Altered metabolic pathways and bioenergetics, microvascular deficits and small vessel disease, chronic inflammation, and excessive tissue remodelling are in focus of this article as evidence-based targets for a predictive approach to develop diagnosis and treatment algorithms tailored to the individual for a cost-effective early prevention by implementing the paradigm shift from reactive medicine to predictive, preventive, and personalized medicine (PPPM) in primary and secondary DR care management.
- Klíčová slova
- Analytical tools, Biomarkers, Blindness, Cell death, Cerebral small vessel disease, Comorbidities, Diabetes mellitus, Diabetic complications, Domino effect, Global burden, Health policy, Health-to-disease transition, Inflammation, Ischemic stroke, Metabolic and signalling shifts, Mitochondrial injury, Molecular patterns, Neovascularisation, Predictive, preventive, and personalised medicine (3P/PPPM), Primary and secondary prevention, Proliferative diabetic retinopathy, ROS, Retinopathy, Stress, Tear fluid,
- Publikační typ
- časopisecké články MeSH
- přehledy MeSH